import datetime 
import pandas as pd
import numpy as np 
import graphistry
import math 

graphistry.register(api=3, personal_key_id='', personal_key_secret='', server='...') 

num_recs=353
num_edges=787

ndf = pd.DataFrame({'ID' : range(num_recs),
                   'tier' : np.random.randint(1,9,num_recs),
                   'FL_risk_exposure' : np.random.randint(0,100,num_recs),
                   'risk_level' : [np.random.choice(['no_risk', 'high_risk', 'med_risk']) for i in range(num_recs)], 
                   'flagged_company' : [np.random.choice(['Yes', 'No']) for i in range(num_recs)], 
                   'rating' : np.random.randint(0,10,num_recs)})

edf = pd.DataFrame({'source' : np.random.choice(10,num_edges),
                    'target' : np.random.choice(10,num_edges)})

tier2len = ndf.tier.value_counts().to_dict()

ndf['x'] = ndf.apply(lambda row: (row['tier']) * math.cos(2*math.pi * row['ID']/tier2len[row['tier']] ), axis=1)
ndf['y'] = ndf.apply(lambda row: (row['tier']) * math.sin(2*math.pi * row['ID']/tier2len[row['tier']]), axis=1)
 

g3 = (graphistry.addStyle(bg={'color': '#F2F7F8'})
                .nodes(ndf, 'ID')
                .edges(edf, 'source', 'target')
                .settings(url_params={'play': 0,'pointSize': .3,'edgeOpacity': .1}, height=800)
                .encode_axis([
                    {'r': 1, 'space': True, "label": "Tier 1"},
                    {'r': 2, 'space': True, "label": "Tier 2"},
                    {'r': 3, 'space': True, "label": "Tier 3"},
                    {'r': 4, 'space': True, "label": "Tier 4"},
                    {'r': 5, 'space': True, "label": "Tier 5"},
                    {'r': 6, 'space': True, "label": "Tier 6"},
                    {'r': 7, 'space': True, "label": "Tier 7"},
                    {'r': 8, 'space': True, "label": "Tier 8"},
                    {'r': 9, 'space': True, "label": "Tier 9"}])
                .encode_point_color('risk_level', as_categorical=True,
                                    categorical_mapping={
                    # 'no_risk' : 'black',
                    'high_risk' : 'red',
                    'med_risk' : 'red'}, default_mapping='black')
     )

g3.plot()